code: def _create_regular_point_cloud(
      height: int,
      width: int,
      num_ray_points: int,
      device: Device,
      dtype: torch.dtype,
  ) -> Tensor:
      x = torch.linspace(
          0, width, steps=width, device=device, dtype=dtype
      )
      y = torch.linspace(
          0, height, steps=height, device=device, dtype=dtype
      )
      xy = torch.meshgrid(y, x, indexing="ij")
      z = torch.linspace(
          1, 11, steps=num_ray_points, device=device, dtype=dtype
      )
      points3d = torch.zeros(
          height, width, num_ray_points, 3, device=device, dtype=dtype
      )
      points3d[..., 0] = xy[0].unsqueeze(-1)
      points3d[..., 1] = xy[1].unsqueeze(-1)
      points3d[..., 2] = z
      return points3d
  
file_path: kornia/test/nerf/test_renderer.py
imports: import math
  import torch
  from kornia.core import Device, Tensor
  from kornia.nerf.volume_renderer import IrregularRenderer, RegularRenderer
  from kornia.testing import assert_close
label_desc: Use image node_id 1 for calling a global function with example usage: _create_regular_point_cloud(height, width, num_ray_points, device, dtype) and returns: points3d